Chemical safety production monitoring method and system

Abstract

The invention provides a chemical safety production monitoring method and system, and is suitable for the technical field of data processing, and the method comprises the steps: generating chemical production feature information according to chemical production environment information, chemical production equipment state information and a chemical production information feature extraction model; generating chemical production monitoring information according to the chemical production feature information, the chemical production feature coding vector and the chemical production monitoring feature mapping vector; and generating chemical production risk degree characterization information according to the chemical production monitoring information and the chemical safety production index information so as to carry out chemical safety production monitoring. According to the method, the multi-source information is integrated to effectively monitor the chemical production link, the key features of the multi-source information are deeply mined through the chemical production information feature extraction model, and the key features are efficiently converted to ensure the accuracy and practicability of the generated chemical production monitoring information, so that potential risks are timely found, and the safety of chemical production is improved. And the chemical production safety is powerfully guaranteed.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and in particular relates to a chemical production safety monitoring method and system. Background Art

[0002] As a key pillar of the national economy, the chemical industry involves numerous complex processes and equipment, making safe production crucial. In recent years, with the continuous expansion of chemical production and the increasing complexity of production processes, traditional methods relying on manual inspections and simple instrument monitoring have become insufficient.

[0003] Existing chemical production safety monitoring solutions usually use sensors to collect chemical production environment parameters (such as temperature, pressure, etc.) and production equipment status information, and then compare these data with pre-set production safety indicators. If the data exceeds the production safety indicator range, an alarm will be issued to remind staff to take measures.

[0004] However, existing technologies are only used to monitor data in a single dimension, which makes it difficult to fully reflect the complex situation of chemical production. In addition, they have limited data processing and analysis capabilities and lack dynamic adaptability to complex production scenarios. They cannot guarantee the timeliness and accuracy of production safety monitoring in the chemical industry. Summary of the Invention

[0005] In view of this, the embodiments of the present application provide a chemical production safety monitoring method and system, which aims to solve the problems existing in existing chemical production monitoring methods, such as difficulty in comprehensively monitoring production conditions, inability to monitor potential risks in the chemical production process, low adaptability to dynamically changing chemical production scenarios, and inability to meet the timeliness and accuracy requirements of chemical production safety monitoring.

[0006] A first aspect of the embodiments of the present application provides a chemical production safety monitoring method, comprising:

[0007] Obtain chemical production environment information, chemical production equipment status information, and chemical production safety index information;

[0008] Generate target chemical production feature information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information feature extraction model;

[0009] Generating chemical production monitoring information according to the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors;

[0010] Based on the chemical production monitoring information and chemical production safety index information, chemical production risk level characterization information is generated, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

[0011] A second aspect of the embodiments of the present application provides a chemical production safety monitoring system, comprising:

[0012] Chemical production information acquisition module, used to obtain chemical production environment information, chemical production equipment status information and chemical production safety index information;

[0013] a target chemical production characteristic information generation module, configured to generate target chemical production characteristic information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information characteristic extraction model;

[0014] a chemical production monitoring information generation module, configured to generate chemical production monitoring information based on the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors;

[0015] The chemical production risk level characterization information generation module is used to generate chemical production risk level characterization information based on the chemical production monitoring information and chemical production safety index information, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

[0016] The third aspect of an embodiment of the present application provides a terminal device, which includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the chemical production safety monitoring method described in the first aspect above.

[0017] Compared with the prior art, the beneficial effects of the embodiments of the present application are as follows: the present application comprehensively obtains multi-source information composed of chemical production environment information and equipment status information for reflecting the current status of chemical production workshops, deeply mines key data features in the multi-source information through the chemical production information feature extraction model, generates target chemical production feature information, and can accurately mine and capture potential risk information in the chemical production process to comprehensively reflect the complex and changeable potential risk conditions in the chemical production environment. Combined with the chemical production feature coding vector and the chemical production monitoring feature mapping vector, the target chemical production feature information is converted into accurate and readable chemical production monitoring information to intuitively reflect the current safety monitoring situation of the chemical production environment, and then by generating chemical production risk degree characterization information, the production risk situation is quantified to achieve real-time and accurate assessment of the chemical production safety situation, and can predict potential risks in the chemical production process in advance, effectively improving the comprehensiveness, accuracy and dynamic adaptability of chemical production safety monitoring, and providing a solid and reliable technical guarantee for the safe production of chemical enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 1 of the present application;

[0020] Figure 2 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 2 of the present application;

[0021] Figure 3 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 3 of the present application;

[0022] Figure 4 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 4 of the present application;

[0023] Figure 5 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 5 of the present application;

[0024] Figure 6 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 6 of the present application;

[0025] Figure 7 This is a schematic diagram of the implementation process of the chemical production safety monitoring method provided in Example 7 of the present application;

[0026] Figure 8 This is a schematic diagram of the structure of the chemical production safety monitoring system provided in the embodiment of the present application;

[0027] Figure 9 It is a schematic diagram of the terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, systems, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0029] In order to illustrate the technical solution described in this application, specific embodiments are provided below.

[0030] Figure 1 The following is a flowchart of the chemical production safety monitoring method provided in Example 1 of the present application, which is described in detail as follows:

[0031] Step S101, obtaining chemical production environment information, chemical production equipment status information and chemical production safety index information.

[0032] In this embodiment, chemical production environment information may refer to temperature information, pressure information, humidity information, harmful gas concentration information and other information collected in real time in the chemical production environment, which can be used to reflect chemical production safety and chemical product quality, and can be collected and obtained in real time through temperature sensors, pressure sensors, gas detectors and other equipment deployed in key areas such as production workshops and reactors; chemical production equipment status information may refer to the operating parameters of chemical production equipment, such as speed, vibration frequency, operating power, etc., or may refer to the working status of chemical production equipment, such as on or off or standby, which can be obtained through vibration sensors, current sensors, infrared thermal imagers, etc. deployed on the surface of chemical production equipment or deployed inside chemical production equipment; chemical production safety index information may be safety thresholds specified by industry standards or enterprise production specifications, such as temperature upper limit, pressure safety range, harmful gas concentration allowable value, etc., which can be obtained by retrieving documents related to production safety in the enterprise safety management system.

[0033] Step S102 : generating target chemical production feature information according to the chemical production environment information, chemical production equipment status information, and a preset chemical production information feature extraction model.

[0034] In this embodiment, the preset chemical production information feature extraction model can be manually set, or it can be a convolutional neural network model, or it can be a model based on the transformer architecture. When the preset chemical production information feature extraction model is a convolutional neural network model or a model based on the transformer architecture, the default is a trained model. The chemical production environment information and the chemical production equipment status information can be first subjected to noise removal by a sliding average filtering method and the default values can be supplemented by a mean interpolation method, and then used as input information of the chemical production information feature extraction model. After calculation by the chemical production information feature extraction model, the output information of the chemical production information feature extraction model is used as the target chemical production feature information. The chemical production information feature extraction model can be used to deeply mine the key data features in multi-source information and the relationship between multiple key data features, such as the relationship between the production environment and the equipment status. It is understandable that when the temperature in the production environment rises, the operating pressure of certain chemical production equipment will increase. When the ambient humidity is high, it may accelerate the corrosion of the metal parts of the equipment, affecting the sealing of the equipment, and thus increasing the risk of material leakage. For example, the relationship between different production equipment. It is understandable that in chemical production, multiple chemical production equipment work together. For example, there is a relationship between the stirring speed of the reactor and the flow rate of the material delivery pump. A stirring speed that is too fast or too slow may affect the mixing effect of the material, and then require the delivery pump to adjust the flow rate accordingly to ensure the material is mixed. To ensure the smooth progress of subsequent reactions, for example, the top temperature and bottom temperature of the distillation tower are closely related to the working conditions of the reboiler and condenser. The parameters between the distillation tower, reboiler and condenser need to match each other to achieve an efficient separation process; for example, the relationship between equipment failure and production abnormalities. It is understandable that some minor failures of chemical production equipment may cause abnormal conditions in the production process. Taking the abnormal vibration of the compressor as an example, the abnormal vibration of the compressor may indicate blockage of the pipeline system or instability of the gas flow, which may further lead to fluctuations in the entire production process and affect product output and quality. By timely excavating and capturing the above potential associations, technical personnel in the chemical production field can be reminded to take maintenance measures in advance to avoid production accidents.

[0035] Step S103 : generating chemical production monitoring information according to the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors.

[0036] In this embodiment, a plurality of preset chemical production feature coding vectors can be manually set, or can be designed based on one-hot coding, or can be designed based on frequency coding, or can be designed based on embedded coding, wherein each preset chemical production feature coding vector is different from each other. A plurality of preset chemical production monitoring feature mapping vectors can be manually set, or can be designed based on a nonlinear mapping method, or can be designed based on a kernel function mapping method. The target chemical production feature information can be first encoded through a plurality of preset chemical production feature coding vectors to obtain the encoded chemical production feature information, and then the encoded chemical production feature information is mapped through a plurality of preset chemical production monitoring feature mapping vectors in a specific order, and the mapped result is output as the chemical production monitoring information.

[0037] Among them, the encoding processing can be to first convert the target chemical production feature information into a vector form based on the bag-of-words model, and then perform a convolution operation on the vector generated by the target chemical production feature information and the chemical production feature encoding vector, or it can be to perform an inner product operation on the vector generated by the target chemical production feature information and the chemical production feature encoding vector; the mapping processing can be to multiply the encoded chemical production feature information with the first chemical production monitoring feature mapping vector, and then multiply the multiplication result with the second chemical production monitoring feature mapping vector, and so on, until all chemical production monitoring feature mapping vectors are calculated, and the final calculation result is used as the vector corresponding to the chemical production monitoring information, and then the vector is converted into text information through a language model such as GPT, and the text information is output as chemical production monitoring information.

[0038] Step S104 , generating chemical production risk level characterization information based on the chemical production monitoring information and chemical production safety index information, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

[0039] In this embodiment, the chemical production monitoring information and the chemical production safety index information may be compared to calculate the degree of deviation between the chemical production monitoring information and the chemical production safety index information. Then, a set of weight values may be pre-set, and the weighted sum of the values of each degree of deviation may be calculated using the set of weight values. The calculation result may be used as the chemical production risk level representation information. The risk level may be divided into different levels, such as low risk, medium risk, and high risk, and a corresponding threshold value may be set for each level to determine whether the chemical production risk level characterization information falls within the corresponding threshold range. For example, the risk level between 0 and 30 is low risk, 31 to 60 is medium risk, and 61 and above is high risk. Chemical production safety monitoring may be carried out through the chemical production risk level characterization information. When the chemical production risk level characterization information is within the medium risk numerical range, an early warning notification may be automatically sent to the management personnel and other staff of the chemical production workshop through sound or text message. When the chemical production risk level characterization information is within the high risk numerical range, a sound alarm function may be automatically turned on in the chemical production workshop to attract the attention of personnel from all parts of the chemical enterprise. At the same time, the risk areas and changes in related indicators may be highlighted on the large screen of the production monitoring center so that personnel can be quickly organized to conduct detailed inspections and emergency response.

[0040] The chemical production safety monitoring method provided in the embodiment of the present application comprehensively obtains multi-source information composed of chemical production environment information and equipment status information for reflecting the current status of the chemical production workshop, deeply mines the key data features in the multi-source information through the chemical production information feature extraction model, and generates target chemical production feature information. It can accurately mine and capture potential risk information in the chemical production process to comprehensively reflect the complex and changeable potential risk conditions in the chemical production environment, and combines the chemical production feature coding vector and the chemical production monitoring feature mapping vector to convert the target chemical production feature information into accurate and readable chemical production monitoring information to intuitively reflect the current safety monitoring situation of the chemical production environment, and then quantify the production risk situation by generating chemical production risk degree characterization information to achieve real-time and accurate assessment of the chemical production safety situation, and can predict potential risks in the chemical production process in advance, effectively improving the comprehensiveness, accuracy and dynamic adaptability of chemical production safety monitoring, and providing a solid and reliable technical guarantee for the safe production of chemical enterprises.

[0041] Figure 2 The following is a flowchart of the chemical production safety monitoring method provided in Example 2 of the present application, which differs from the above-mentioned Example 1 in that:

[0042] The preset chemical production information feature extraction model includes a plurality of preset chemical production information feature extraction sub-models, a plurality of preset chemical production information feature extraction sub-model selection functions, and a plurality of preset chemical production information feature enhancement functions; wherein the preset chemical production information feature extraction sub-models correspond one to one with the preset chemical production information feature extraction sub-model selection functions;

[0043] The step S102 specifically includes:

[0044] Step S201 : obtaining a plurality of chemical production information feature extraction sub-model selection weight information according to the chemical production environment information, chemical production equipment status information and a plurality of preset chemical production information feature extraction sub-model selection functions.

[0045] In this embodiment, when the preset chemical production information feature extraction model is a model based on the transformer architecture, the preset chemical production information feature extraction sub-model can be a transformer model. The preset chemical production information feature extraction sub-model selection function can be artificially set to quantify the adaptability of chemical production environment information, chemical production equipment status information and each chemical production information feature extraction sub-model. It can be that the chemical production environment information and chemical production equipment status information are first converted into two vectors, and the two vectors are spliced, and the spliced vectors are used as the independent variables of multiple chemical production information feature extraction sub-model selection functions, and the function value obtained by calculating the chemical production information feature extraction sub-model selection function is used as the selection weight information of multiple chemical production information feature extraction sub-models. It can be understood that one chemical production information feature extraction sub-model selection function can calculate a chemical production information feature extraction sub-model selection weight information, and multiple chemical production information feature extraction sub-model selection functions can calculate multiple chemical production information feature extraction sub-model selection weight information.

[0046] Step S202 , performing standardization processing on the selection weight information of the plurality of chemical production information feature extraction sub-models to obtain standardized selection weight information of the plurality of chemical production information feature extraction sub-models.

[0047] In this embodiment, the chemical production information feature extraction sub-model selection weight information can be standardized by Z-score standardization to scale the value range of each chemical production information feature extraction sub-model selection weight information to the interval [0, 1] to avoid large calculation errors caused by the numerical value exceeding the computer's dimensional requirements in subsequent calculations. The standardized information is then used as the chemical production information feature extraction sub-model standardized selection weight information.

[0048] Step S203 , calculating and obtaining a plurality of chemical production information characteristic variable information based on the chemical production environment information, the chemical production equipment status information, and a plurality of preset chemical production information feature extraction sub-models.

[0049] In this embodiment, chemical production environment information and chemical production equipment status information can be first converted into two vectors, which are then concatenated. The concatenated vectors are then used as input vectors for multiple chemical production information feature extraction sub-models. After calculations by the multiple chemical production information feature extraction sub-models, the output results of the multiple chemical production information feature extraction sub-models are used as multiple chemical production information feature variable information. The multiple chemical production information feature extraction sub-models can be used to extract key information from the chemical production environment information and chemical production equipment status information from different dimensions, and potential connections between the key information can be mined and captured. Specifically, the potential connection between key information, such as the connection between the production environment and the equipment status, that is, the temperature, humidity and other factors in the chemical production environment may be closely related to the operating status of the production equipment. When the ambient temperature is too high, it may cause the equipment to have difficulty in heat dissipation, and then the temperature of the key components of the equipment will rise, affecting its performance and life. Therefore, once the potential connection between the ambient temperature and the temperature of the key components of the equipment is found, measures can be taken in advance, such as strengthening ventilation and heat dissipation, to avoid equipment failure due to overheating and ensure stable production; for example, the connection between different production equipment, that is, chemical production usually involves the coordinated work of multiple equipment, and the operating status of different equipment also has potential connections. In a production process consisting of a reactor, a distillation tower and a compressor, the pressure change of the reactor may affect the separation effect of the distillation tower, and the load change of the distillation tower will affect the working status of the compressor, and timely capture By understanding the relationship between reactors, distillation towers, and compressors, the overall production process can be coordinated and optimized during chemical production, and problems that may arise due to the mutual influence between equipment can be discovered and resolved in a timely manner. For example, the relationship between equipment failures and maintenance records, that is, the frequency and type of equipment failures are often potentially associated with past maintenance records. When a chemical production equipment has not been maintained according to the prescribed maintenance cycle for a long time, or there are certain links that have not been handled properly in past maintenance, the probability of failure of the chemical production equipment will increase, and the type of failure may be related to improperly maintained parts or links. By mining and capturing the relationship between equipment failures and maintenance records, technical personnel in the chemical production field can specify more reasonable equipment maintenance plans, so as to inspect and maintain equipment that may fail in advance, prevent failures, and reduce production interruptions and losses caused by equipment failures.

[0050] Step S204 , performing weighted summation on the plurality of chemical production information characteristic variable information based on the standardized selection weight information of the plurality of chemical production information characteristic extraction sub-models to generate initial chemical production characteristic information.

[0051] In this embodiment, the standardized selection weight information of each chemical production information feature extraction sub-model may be matched with the output result of each chemical production information feature extraction sub-model, and then a weighted sum calculation may be performed, and the calculation result may be used as the initial chemical production feature information.

[0052] Step S205 : generating target chemical production characteristic information according to the initial chemical production characteristic information and a plurality of preset chemical production information characteristic enhancement functions.

[0053] In this embodiment, the preset chemical production information feature enhancement function can be manually designed, or can be designed based on a weighted adjustment mechanism to highlight key information in the chemical production feature information; it can be a noise reduction filter function that uses algorithms such as mean filtering and median filtering to improve the purity and reliability of feature information for noise and outliers in the data; it can also be a feature fusion function that combines related chemical production information features to explore potential feature relationships and enhance the expressiveness of chemical production information features. It can be that the initial chemical production feature information is used as the independent variable of multiple chemical production information feature enhancement functions, and based on preset weight information, the function values calculated by the multiple chemical production information feature enhancement functions are weighted summed, and the result of the weighted sum is used as the target chemical production feature information.

[0054] The chemical production safety monitoring method provided in the embodiment of the present application calculates the standardized selection weight information of multiple chemical production information feature extraction sub-models, quantifies the adaptability of chemical production environment information, chemical production equipment status information and each chemical production information feature extraction sub-model, extracts key features in chemical production environment information and chemical production equipment status information from multiple dimensions through multiple different chemical production information feature extraction sub-models, avoids the limitation caused by a single model can only extract features of a single or limited number of dimensions, generates initial chemical production feature information through weighted summation, integrates the advantages of multiple chemical production information feature extraction sub-models, comprehensively extracts various information features of chemical production information, and then introduces a chemical production information feature enhancement function to eliminate the noise components in the initial chemical production feature information, enhance key features and explore the potential correlation between various feature information, thereby providing an effective data basis for the subsequent generation of accurate chemical production monitoring information, effectively improving the efficiency and accuracy of chemical production safety monitoring, and safeguarding chemical production safety.

[0055] Figure 3The following is a flowchart of the chemical production safety monitoring method provided in Example 3 of the present application, which differs from the above-mentioned Example 2 in that:

[0056] The plurality of preset chemical production information feature enhancement functions include a preset first chemical production information feature enhancement function, a preset second chemical production information feature enhancement function, a preset third chemical production information feature enhancement function, and a preset fourth chemical production information feature enhancement function;

[0057] The step S205 specifically includes:

[0058] Step S301, based on the initial chemical production characteristic information, the preset first chemical production information characteristic enhancement function, the preset second chemical production information characteristic enhancement function and the preset third chemical production information characteristic enhancement function, calculate the first chemical production characteristic enhancement representation information, the second chemical production characteristic enhancement representation information and the third chemical production characteristic enhancement representation information.

[0059] In this embodiment, the preset chemical production information feature enhancement function can be artificially designed. Among them, the first chemical production information feature enhancement function can be a dimension that focuses on the correlation between the chemical production environment and the equipment operating status. In actual chemical production operations, by deeply analyzing the data such as the chemical production environment temperature, humidity and the temperature of key components of chemical production equipment, the first chemical production feature enhancement representation information is obtained. The first chemical production feature enhancement representation information can be used to reflect the correlation characteristics between the corrosion rate of chemical production equipment made of certain metal materials and the environmental humidity and temperature in a high temperature and humid environment. It can help predict the equipment corrosion risk, take protective measures in advance, and ensure the safe and stable operation of chemical production equipment; the second chemical production information feature enhancement function can be to focus on exploring the potential logical relationship between the parameters of each link in the chemical production process. Taking the reaction temperature, pressure, raw material ratio and other parameters of the reactor as an example, it can be analyzed by Analyze how the reaction temperature, pressure, raw material ratio and other parameters of the reactor affect each other to achieve the best reaction effect, and obtain the second chemical production feature enhancement representation information. The second chemical production feature enhancement representation information can be used to timely detect abnormal parameter fluctuations, optimize the production process, and avoid product quality degradation or production accidents due to unreasonable parameters; the third chemical production information feature enhancement function can be analyzed from the dimension of comparing historical equipment failure data with the current operating status, and can be obtained by comparing real-time data such as vibration frequency and noise of chemical production equipment with similar features in historical failure data. The third chemical production feature enhancement representation information can be used to identify early signs of equipment failure in advance, realize preventive maintenance, reduce chemical production equipment downtime, and improve chemical production efficiency.

[0060] In this embodiment, optionally, the chemical production environment characteristic information and the chemical production equipment status characteristic information in the initial chemical production characteristic information can be first extracted as the independent variables of the first chemical production information characteristic enhancement function, and the correlation between the chemical production environment characteristic information and the chemical production equipment status characteristic information is calculated through the first chemical production information characteristic enhancement function. Then, the first chemical production information characteristic enhancement function can be designed based on the calculation method of the Spearman correlation coefficient or the Pearson correlation coefficient. Then, the first chemical production characteristic enhancement representation information quantifies the correlation between the chemical production environment characteristic information and the chemical production equipment status characteristic information; it can be to extract parameters related to the production process from the initial chemical production characteristic information, such as the reaction temperature, pressure, and raw material ratio information of the reactor as the independent variables of the second chemical production information characteristic enhancement function, and the second chemical production information characteristic enhancement function is used to mine the interactions and influences between multiple parameters related to the production process. Then, the first chemical production information characteristic enhancement function can be designed based on the calculation method of the Spearman correlation coefficient or the Pearson correlation coefficient. Then, the first chemical production characteristic enhancement representation information quantifies the correlation between the chemical production environment characteristic information and the chemical production equipment status characteristic information. The second chemical production information feature enhancement function can be designed based on the decision tree algorithm, and the second chemical production feature enhancement representation information calculated by the second chemical production information feature enhancement function can be used to quantify product quality or reaction yield; it can be the real-time operation information of the chemical production equipment extracted from the initial chemical production feature information, such as vibration frequency, etc. as the independent variable of the third chemical production information feature enhancement function, and the third chemical production information feature enhancement function is used to quantify the similarity between the current operation information of the chemical production equipment and the past operation information of the chemical production equipment. The third chemical production information feature enhancement function can be designed based on cosine similarity or pattern recognition algorithm, and the third chemical production feature enhancement representation information calculated by the third chemical production information feature enhancement function is used to quantify the similarity between the current operation information of the chemical production equipment and the past operation information of the chemical production equipment, providing high-value feature basis for subsequent chemical production monitoring and risk assessment.

[0061] Step S302: Calculate chemical production feature enhancement weight information based on the first chemical production feature enhancement representation information and the second chemical production feature enhancement representation information.

[0062] In this embodiment, the judgment of human experts can be introduced to score the first chemical production characteristic enhancement representation information and the second chemical production characteristic enhancement representation information. That is, through the experience of human experts in the field of chemical production, in the actual chemical production process, which type of chemical production information is more strongly correlated with the occurrence of actual risk events and has a higher frequency of occurrence, and which type of chemical production characteristic enhancement representation information has a higher score value. The score value is normalized and used as the chemical production characteristic enhancement weight information, which is used to reflect the relative importance of the first chemical production characteristic enhancement representation information and the second chemical production characteristic enhancement representation information in the comprehensive analysis.

[0063] Step S303: generating target chemical production feature information according to the chemical production feature enhancement weight information and the third chemical production feature enhancement representation information.

[0064] In this embodiment, the chemical production feature enhancement weight information can be used as a key basis for measuring the contribution of the third chemical production feature enhancement representation information in the final target feature information. Based on the chemical production feature enhancement weight information, the third chemical production feature enhancement representation information is targetedly adjusted and optimized. If the chemical production feature enhancement weight information indicates that the first chemical production feature enhancement representation information and the second chemical production feature enhancement representation information are more important, then when integrating the third chemical production feature enhancement representation information, more attention is paid to the fit and coordination of the third chemical production feature enhancement representation information with the first chemical production feature enhancement representation information and the second chemical production feature enhancement representation information. Conversely, if the chemical production feature enhancement weight information shows that the third chemical production feature enhancement representation information is more critical, the third chemical production feature enhancement representation information is given a higher priority to highlight the role of the third chemical production feature enhancement representation information in the final feature information. Then, the adjusted third chemical production feature enhancement representation information is deeply integrated with the first chemical production feature enhancement representation information and the second chemical production feature enhancement representation information according to the ratio set by the weight, so as to comprehensively consider the actual needs of chemical production and the logical relationship between various types of information, so that the feature enhancement information of different dimensions complements and synergizes with each other to generate the target chemical production feature information.

[0065] In this embodiment, the target chemical production characteristic information can comprehensively consider multiple factors such as the production environment, equipment operation, and production process, determine whether the current production process has a high risk, and the source of the risk, and provide comprehensive and accurate information support for formulating corresponding risk control measures. The target chemical production characteristic information can be used to reflect the nonlinear relationship between the various features of the initial chemical production characteristic information. For example, it can reflect the nonlinear relationship between the chemical production environment and the operating status of the chemical production equipment, that is, the impact of temperature, humidity, pressure, etc. on the operation of the equipment, and whether the operating parameters of the equipment itself are normal, whether there is a potential failure risk, etc.; it can reflect the logical relationship between the parameters of the chemical production process, and can be used to determine whether the production process is in a stable and efficient operating state, and when a parameter is abnormal, the chain reaction that may occur to other parameters and the entire production process; it can reflect the relationship between the historical failure of the chemical equipment and the current state, that is, what are the similarities or differences between the current state of the equipment and the state when the failure occurred in the past, and can be used to remind chemical production field staff to take measures in advance for possible failures of the chemical production equipment.

[0066] The chemical production safety monitoring method provided in the embodiment of the present application, first, initializes chemical production characteristic information through parallel processing of multiple chemical production information feature enhancement functions, and deeply mines and optimizes the initial chemical production characteristic information from different dimensions, thereby realizing multi-angle enhancement of chemical production characteristic information and effectively enriching the connotation of chemical production characteristic information; secondly, by calculating the chemical production feature enhancement weight information, the importance of different feature enhancement directions is accurately quantified, and the contribution ratio of each enhancement direction can be automatically adjusted in combination with the actual chemical production information characteristics, so that the enhancement process of chemical production characteristic information is more flexible and targeted, so as to effectively balance the influence of different feature enhancement paths, and ensure that the characteristic information finally generated can accurately reflect the key elements of chemical production, thereby fully tapping the potential value of chemical production data and effectively suppressing interference factors, thereby significantly improving the accuracy and effectiveness of chemical production safety monitoring.

[0067] Figure 4 The following is a flowchart of a method for monitoring chemical production safety provided in Example 4 of the present application, which differs from Example 1 above in that:

[0068] The plurality of preset chemical production feature coding vectors include a preset chemical production monitoring local feature coding vector and a preset chemical production monitoring long-range feature coding vector;

[0069] The plurality of preset chemical production monitoring feature mapping vectors include a preset chemical production monitoring feature search mapping vector, a preset chemical production monitoring feature classification mapping vector, a preset chemical production monitoring feature semantic mapping vector, and a plurality of preset chemical production monitoring mapping feature reconstruction vectors;

[0070] The step S103 specifically includes:

[0071] Step S401 : obtaining a chemical production local feature coding vector according to the target chemical production feature information and a preset chemical production monitoring local feature coding vector.

[0072] In this embodiment, the preset chemical production monitoring local feature coding vector can be manually set and can be used to focus on feature information within a local range of the chemical production process. The target chemical production feature information can be converted into a vector and then an inner product operation is performed with the chemical production monitoring local feature coding vector, with the result of the operation being used as the chemical production local feature coding vector.

[0073] Step S402 : obtaining a chemical production long-range characteristic coding vector according to the target chemical production characteristic information and a preset chemical production monitoring long-range characteristic coding vector.

[0074] In this embodiment, the preset long-range chemical production monitoring feature coding vector can be manually set to reflect long-term trends and global information in the chemical production process. The target chemical production feature information can be converted into a vector and then an inner product operation is performed with the long-range chemical production monitoring feature coding vector, with the result of the operation being used as the local chemical production feature coding vector.

[0075] Step S403 , interleaving and splicing the local feature coding vector of chemical production and the long-range feature coding vector of chemical production to obtain a chemical production feature coding vector.

[0076] In this embodiment, the elements in the local feature coding vector of chemical production and the long-range feature coding vector of chemical production may be alternately arranged according to an artificially set splicing rule to form a new vector as the chemical production feature coding vector.

[0077] Step S404 , performing convolution calculation based on the chemical production feature coding vector and the preset chemical production monitoring feature search mapping vector to obtain chemical production search mapping feature vector information.

[0078] In this embodiment, the preset chemical production monitoring feature search mapping vector can be manually set and used to search the chemical production feature encoding vector for feature information related to the search mapping vector. The chemical production feature encoding vector can be convolved with the chemical production monitoring feature search mapping vector, and the result of the convolution operation can be used as the chemical production search mapping feature vector information.

[0079] Step S405 , performing convolution calculation based on the chemical production feature coding vector and the preset chemical production monitoring feature classification mapping vector to obtain chemical production classification mapping feature vector information.

[0080] In this embodiment, the preset chemical production monitoring feature classification mapping vector can be manually set and used to find feature information related to the classification mapping vector within the chemical production feature encoding vector. This can be accomplished by performing a convolution calculation on the chemical production feature encoding vector and the chemical production monitoring feature classification mapping vector, with the result being the chemical production classification mapping feature vector information.

[0081] Step S406 , performing convolution calculation based on the chemical production feature coding vector and the preset chemical production monitoring feature semantic mapping vector to obtain chemical production semantic mapping feature vector information.

[0082] In this embodiment, the preset chemical production monitoring feature semantic mapping vector can be manually set to capture semantically meaningful feature information in chemical production, thereby extracting related semantic feature information from the chemical production feature encoding vector. The chemical production feature encoding vector can be convolved with the result, and the result is used as the chemical production semantic mapping feature vector information.

[0083] Step S407 , performing inner product operation and dimensionality reduction processing on the chemical production search mapping feature vector information and the chemical production classification mapping feature vector information to obtain chemical production mapping feature intermediate variable information.

[0084] In this embodiment, the chemical production search mapping feature vector information and the chemical production classification mapping feature vector information can be first subjected to an inner product operation, and then the result of the inner product operation can be subjected to dimensionality reduction processing to a vector with the same dimension as the chemical production classification mapping feature vector information. The vector after dimensionality reduction is then used as the chemical production mapping feature intermediate variable information.

[0085] Step S408 : performing fusion processing on the chemical production mapping feature intermediate variable information and the chemical production semantic mapping feature vector information to obtain chemical production mapping feature vector information.

[0086] In this embodiment, the weighted average and vector splicing methods can be used to fuse the chemical production mapping feature intermediate variable information and the chemical production semantic mapping feature vector information, organically combine the chemical production mapping feature intermediate variable information and the chemical production semantic mapping feature vector information, and use the fused vector as the chemical production mapping feature vector information.

[0087] Step S409 : generating chemical production monitoring information according to the chemical production mapping feature vector information and a plurality of preset chemical production monitoring mapping feature reconstruction vectors.

[0088] In this embodiment, the preset chemical production monitoring local feature coding vector may be artificially designed, and the chemical production mapping feature vector information may be multiplied by a plurality of chemical production monitoring mapping feature reconstruction vectors, and the calculated result is used as the chemical production monitoring information.

[0089] The chemical production safety monitoring method provided in the embodiment of the present application decomposes the target chemical production characteristic information into local characteristics and long-range characteristics and encodes them separately. The local data of chemical production equipment, chemical production environment area, etc. are focused on through the local characteristic coding vector of chemical production monitoring to capture immediate risk information. The long-range characteristic coding vector of chemical production monitoring is used to integrate long-term production data and mine trend risks. The local characteristic information and long-range characteristic information are interleaved and spliced to generate the chemical production characteristic coding vector, thereby achieving full coverage of the spatiotemporal dimension of chemical production information and improving the comprehensiveness of chemical production process information monitoring. Furthermore, the key characteristics are actively retrieved through the convolution calculation of the chemical production monitoring characteristic search mapping vector, and the production status is accurately distinguished through the convolution calculation of the chemical production monitoring characteristic classification mapping vector. State category, convolution calculation is performed on the chemical production monitoring feature semantic mapping vector to capture the feature semantics of chemical production information, so as to achieve a comprehensive and in-depth analysis of the chemical production feature information, and then the core features in the chemical production feature information are effectively refined through inner product operation and dimensionality reduction processing, and redundant information is removed. The multi-dimensional features are further integrated through fusion processing, so that the generated chemical production mapping feature vector information can accurately reflect the potential risks in the chemical production process. The chemical production monitoring mapping feature reconstruction vector is used to transform the abstract chemical production feature vector into chemical production monitoring information that fits the actual production needs, thereby significantly improving the monitoring effectiveness and data analysis depth of the chemical production process, so as to improve the accuracy of risk warning for chemical production and provide comprehensive and reliable data support for chemical production safety monitoring.

[0090] Figure 5 The flowchart of the chemical production safety monitoring method provided in the fifth embodiment of the present application is shown. The difference between the fifth embodiment and the fourth embodiment is that:

[0091] The plurality of preset chemical production monitoring mapping feature reconstruction vectors include a preset first chemical production monitoring mapping feature combination vector, a preset first chemical production monitoring mapping feature transformation vector, a preset second chemical production monitoring mapping feature combination vector, and a preset second chemical production monitoring mapping feature transformation vector;

[0092] The step S409 specifically includes:

[0093] Step S501 : generating initial chemical production mapping feature combination information according to the chemical production mapping feature vector information and a preset first chemical production monitoring mapping feature combination vector.

[0094] In this embodiment, the preset first chemical production monitoring mapping feature combination vector can be manually set. For example, the chemical production mapping feature vector information can be multiplied by the first chemical production monitoring mapping feature combination vector, and the multiplication result can be used as the initial chemical production mapping feature combination information to preliminarily screen out feature combinations that are important for chemical production monitoring.

[0095] Step S502 : generating initialization chemical production mapping feature reconstruction information according to the initialization chemical production mapping feature combination information and a preset first chemical production monitoring mapping feature transformation vector.

[0096] In this embodiment, the preset first chemical production monitoring mapping feature transformation vector may be manually set, and the initial chemical production mapping feature combination information and the first chemical production monitoring mapping feature transformation vector may be added together, and the addition result may be used as the initial chemical production mapping feature reconstruction information.

[0097] Step S503 : generating target chemical production mapping feature combination information according to the initial chemical production mapping feature reconstruction information and the preset second chemical production monitoring mapping feature combination vector.

[0098] In this embodiment, the preset second chemical production monitoring mapping feature combination vector can be manually set. The initial chemical production mapping feature reconstruction information is multiplied by the second chemical production monitoring mapping feature combination vector, and the multiplication result is used as the target chemical production mapping feature combination information.

[0099] Step S504 : generating target chemical production mapping feature reconstruction information according to the target chemical production mapping feature combination information and a preset second chemical production monitoring mapping feature transformation vector.

[0100] In this embodiment, the preset second chemical production monitoring mapping feature transformation vector can be manually set. The target chemical production mapping feature combination information is added to the second chemical production monitoring mapping feature transformation vector, and the addition result is used as the target chemical production mapping feature reconstruction information.

[0101] Step S505 , performing feature space conversion processing on the target chemical production mapping feature reconstruction information to generate chemical production monitoring information.

[0102] In this embodiment, the feature space transformation processing can be performed by linear transformation, nonlinear transformation, autoencoder or variational autoencoder. The target chemical production mapping feature reconstruction information after feature space transformation processing is output as chemical production monitoring information.

[0103] The chemical production safety monitoring method provided in the embodiment of the present application performs multi-level and multi-angle processing on the chemical production mapping feature vector information through multiple groups of chemical production monitoring mapping feature combination vectors and transformation vectors, gradually refines and optimizes the chemical production feature information, avoids the loss or misjudgment of chemical production information that may be caused by a single processing method, improves the accuracy of chemical production monitoring, provides reliable and accurate data support for the safety monitoring and management of chemical production, helps chemical production enterprises to timely discover potential risks, and ensures the stable operation of chemical production.

[0104] Figure 6 The following is a flowchart of a method for monitoring chemical production safety provided in Example 6 of the present application, which differs from the above-mentioned Example 1 in that:

[0105] The chemical production monitoring information includes chemical production environment temperature monitoring information, chemical production environment pressure monitoring information and chemical production equipment operation status monitoring information;

[0106] The chemical production safety index information includes chemical production environment temperature standard interval information, chemical production environment pressure standard interval information and multiple chemical production equipment operating status characterization standard value information;

[0107] The step S104 specifically includes:

[0108] Step S601 , normalizing the chemical production environment temperature monitoring information, the chemical production environment pressure monitoring information, and the chemical production equipment operation status monitoring information to generate a plurality of normalized chemical production safety monitoring information.

[0109] In this embodiment, chemical production environment temperature monitoring information may refer to real-time temperature data within the chemical production environment, which is used to reflect the thermal state of the production environment and has a significant impact on the safety of the chemical production process and product quality. Chemical production environment pressure monitoring information may refer to real-time pressure data within the chemical production environment. Pressure changes can affect the progress of chemical reactions and the safety of equipment. Chemical production equipment operating status monitoring information may refer to operating parameters of chemical production equipment such as speed, vibration frequency, operating power, etc., as well as the equipment's operating status, such as on, off, or standby. Chemical production environment temperature standard range information may refer to the safe range of chemical production environment temperature specified by industry standards or enterprise production specifications, including lower and upper temperature limits. Chemical production environment pressure standard range information may refer to the safe range of chemical production environment pressure specified by industry standards or enterprise production specifications, with minimum and maximum pressure limits. Chemical production equipment operating status representative standard value information may refer to the standard values of various parameters specified in industry standards or enterprise production specifications for measuring the normal operation of chemical production equipment, such as the equipment's standard speed, normal vibration frequency range, rated operating power, etc. The sigmoid function can be used for normalization processing to avoid calculation errors caused by the calculated values exceeding the dimension allowed by the computer system in the subsequent calculation process. The normalized information of chemical production environment temperature monitoring information, chemical production environment pressure monitoring information and chemical production equipment operation status monitoring information is used as multiple normalized information for chemical production safety monitoring.

[0110] Step S602 , calculating and obtaining a plurality of chemical production safety monitoring prediction information based on the plurality of normalized chemical production safety monitoring information and a plurality of preset chemical production safety monitoring information prediction calculation functions.

[0111] In this embodiment, the preset chemical production safety monitoring information prediction calculation function can be manually configured to process chemical production monitoring data with time series characteristics. Multiple pieces of normalized chemical production safety monitoring information can be sequentially used as independent variables of the chemical production safety monitoring information prediction calculation function, and the information calculated by the chemical production safety monitoring information prediction calculation function is output as multiple pieces of chemical production safety monitoring prediction information.

[0112] Step S603, respectively match the multiple chemical production safety monitoring prediction information with the chemical production environment temperature standard interval information, the chemical production environment pressure standard interval information, and the multiple chemical production equipment operating status characterization standard value information to generate chemical production risk level characterization information, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

[0113] In this embodiment, the chemical production environment temperature monitoring and prediction information is determined to determine whether it is within the standard temperature range. For pressure monitoring and prediction information, the pressure monitoring and prediction information is similarly determined to determine whether it is within the standard pressure range. For equipment operating status monitoring and prediction information, the information is compared with the corresponding standard value representing the equipment operating status. Based on the matching results, the degree of deviation of various indicators in the chemical production process from the standard is determined, and then chemical production risk level information is generated to intuitively reflect the level of risk in the chemical production process.

[0114] The chemical production safety monitoring method provided in the embodiment of the present application effectively solves the problem of differences in the dimensions and numerical ranges of different indicators in chemical production monitoring information through normalization processing, making various types of information comparable. Through the chemical production safety monitoring information prediction calculation function, it can fully explore the time series characteristics of chemical production data and accurately capture the dynamic change trends of various indicators in the production process, so as to take targeted measures, effectively reduce the probability of chemical production accidents, and improve the safety of chemical production.

[0115] Figure 7 The following is a flowchart of a method for monitoring chemical production safety provided in Example 7 of the present application, which differs from the above-mentioned Example 1 in that:

[0116] The plurality of preset chemical production safety monitoring information prediction calculation functions include a plurality of preset chemical production safety monitoring information prediction weight parameters and a plurality of preset chemical production safety monitoring information prediction bias parameter information;

[0117] The plurality of preset chemical production safety monitoring information prediction weight parameters include a preset first chemical production safety monitoring information prediction weight parameter, a preset second chemical production safety monitoring information prediction weight parameter, and a preset third chemical production safety monitoring information prediction weight parameter;

[0118] The plurality of preset chemical production safety monitoring information prediction bias parameter information includes preset first chemical production safety monitoring information prediction bias parameter information, preset second chemical production safety monitoring information prediction bias parameter information, and preset third chemical production safety monitoring information prediction bias parameter information;

[0119] The step S103 specifically includes:

[0120] Step S701 : Calculate and obtain a plurality of first chemical production safety monitoring information prediction characteristic variables based on the plurality of normalized chemical production safety monitoring information and preset first chemical production safety monitoring information prediction weight parameters.

[0121] In this embodiment, the preset first chemical production safety monitoring information prediction weight parameter may be manually set. For example, the first chemical production safety monitoring information prediction weight parameter may be multiplied by multiple normalized chemical production safety monitoring information, and the multiplication result may be used as multiple first chemical production safety monitoring information prediction feature variables.

[0122] Step S702 : Calculate and obtain a plurality of first chemical production safety monitoring information prediction feature bias variables based on a plurality of the first chemical production safety monitoring information prediction feature variables and preset first chemical production safety monitoring information prediction bias parameter information.

[0123] In this embodiment, the preset first chemical production safety monitoring information prediction bias parameter information may be manually set. This may be accomplished by adding a plurality of first chemical production safety monitoring information prediction feature variables to the first chemical production safety monitoring information prediction bias parameter information, and using the added result as a plurality of first chemical production safety monitoring information prediction feature bias variables.

[0124] Step S703 , calculating and obtaining a plurality of second chemical production safety monitoring information prediction feature variables based on a plurality of the first chemical production safety monitoring information prediction feature bias variables and a preset second chemical production safety monitoring information prediction weight parameter.

[0125] In this embodiment, the preset second chemical production safety monitoring information prediction weight parameter may be manually set. This may be achieved by multiplying a plurality of first chemical production safety monitoring information prediction feature bias variables by the second chemical production safety monitoring information prediction weight parameter, and using the multiplication result as a plurality of second chemical production safety monitoring information prediction feature variables.

[0126] Step S704 , calculating a plurality of second chemical production safety monitoring information prediction feature variables and preset second chemical production safety monitoring information prediction bias parameter information to obtain a plurality of second chemical production safety monitoring information prediction feature bias variables.

[0127] In this embodiment, the preset second chemical production safety monitoring information prediction bias parameter information may be manually set. This may be accomplished by adding a plurality of second chemical production safety monitoring information prediction feature variables to the second chemical production safety monitoring information prediction bias parameter information, and using the added result as a plurality of second chemical production safety monitoring information prediction feature bias variables.

[0128] Step S705 , calculating and obtaining a plurality of third chemical production safety monitoring information prediction feature variables based on a plurality of the second chemical production safety monitoring information prediction feature bias variables and a preset third chemical production safety monitoring information prediction weight parameter.

[0129] In this embodiment, the preset third chemical production safety monitoring information prediction weight parameter can be manually set. This can be achieved by multiplying multiple second chemical production safety monitoring information prediction feature bias variables with the third chemical production safety monitoring information prediction weight parameter, and using the multiplication results as multiple third chemical production safety monitoring information prediction feature variables.

[0130] Step S706 , calculating the plurality of third chemical production safety monitoring information prediction feature variables and the preset third chemical production safety monitoring information prediction bias parameter information to obtain a plurality of third chemical production safety monitoring information prediction feature bias variables.

[0131] In this embodiment, the preset third chemical production safety monitoring information prediction bias parameter information may be manually set. This may be accomplished by adding multiple third chemical production safety monitoring information prediction feature variables to the third chemical production safety monitoring information prediction bias parameter information, and using the added result as multiple third chemical production safety monitoring information prediction feature bias variables.

[0132] Step S707 , performing hyperbolic tangent transformation on the plurality of third chemical production safety monitoring information prediction feature bias variables to obtain chemical production monitoring feature prediction variables.

[0133] In this embodiment, a hyperbolic tangent transformation may be performed using a hyperbolic tangent function. Multiple third chemical production safety monitoring information prediction feature bias variables may be used as independent variables of the hyperbolic tangent function, and the function values obtained through calculation may be used as chemical production monitoring feature prediction variables. The hyperbolic tangent transformation is used to perform nonlinear transformation on the data, compressing the range of values of each value in the third chemical production safety monitoring information prediction feature bias variable, highlighting the changing trend of each data point, and enhancing the distinguishability of each data point, thereby obtaining chemical production monitoring feature prediction variables, making each value more suitable for subsequent monitoring and prediction.

[0134] Step S708, obtaining multiple chemical production safety monitoring prediction feature information based on the first chemical production safety monitoring information prediction feature bias variable, the second chemical production safety monitoring information prediction feature bias variable, the chemical production monitoring feature prediction variable and the preset chemical production monitoring feature weight information.

[0135] In this embodiment, the preset chemical production monitoring feature weight information can be manually set to represent the reliability and criticality of each prediction feature variable. Based on the chemical production monitoring feature weight information, a weighted summation of the first chemical production safety monitoring information prediction feature bias variable, the second chemical production safety monitoring information prediction feature bias variable, and the chemical production monitoring feature prediction variable can be performed, and the result of the weighted summation is used as multiple chemical production safety monitoring prediction feature information.

[0136] Step S709: performing linear transformation on the plurality of chemical production safety monitoring and prediction feature information to calculate and obtain a plurality of chemical production safety monitoring and prediction information.

[0137] In this embodiment, linear transformation can be performed on multiple chemical production safety monitoring prediction feature information through scaling and translation processing, and the fused feature information can be converted into final chemical production safety monitoring prediction information, so that the prediction information meets the actual application requirements of chemical production monitoring and can intuitively reflect the prediction status of various chemical production indicators.

[0138] The chemical production safety monitoring method provided in the embodiment of the present application performs multiple rounds of weighting and offset adjustment on the normalized chemical production safety monitoring information through multiple sets of preset weight parameters and bias parameter information, thereby deeply exploring the key features in the chemical production monitoring information from multiple dimensions, avoiding the limitations of single weight and bias settings, and fully considering the complexity and correlation of various factors in the chemical production process. By introducing hyperbolic tangent transformation processing, the nonlinear expression ability of each feature data is effectively enhanced, so that the complex change trends and subtle feature differences in the chemical production monitoring data can be amplified, thereby achieving easy capture, improving the accuracy of the prediction, and enabling multiple chemical production safety monitoring prediction information to provide strong data support for chemical production safety monitoring, helping staff to predict production risks in advance and take timely response measures, thereby significantly improving the scientificity and effectiveness of chemical production safety monitoring and ensuring stable operation of chemical production.

[0139] Corresponding to the method of the above embodiment, Figure 8 A structural block diagram of a chemical production safety monitoring system provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown. Figure 8 The exemplary chemical production safety monitoring system may be the execution entity of the chemical production safety monitoring method provided in the aforementioned first embodiment.

[0140] Reference Figure 8 , the chemical production safety monitoring system includes:

[0141] Chemical production information acquisition module 810, used to obtain chemical production environment information, chemical production equipment status information and chemical production safety index information;

[0142] A target chemical production characteristic information generating module 820 is configured to generate target chemical production characteristic information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information characteristic extraction model;

[0143] A chemical production monitoring information generating module 830 is configured to generate chemical production monitoring information based on the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors;

[0144] The chemical production risk level characterization information generation module 840 is used to generate chemical production risk level characterization information based on the chemical production monitoring information and chemical production safety index information, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

[0145] The process of each module realizing its own function in the chemical production safety monitoring system provided in the embodiment of the present application can be specifically referred to the aforementioned Figure 1 The description of the first embodiment will not be repeated here.

[0146] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0147] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0148] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0149] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0150] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish descriptions and should not be understood as indicating or implying relative importance. It should also be understood that although the terms "first", "second", etc. are used in the text to describe various elements in some embodiments of the present application, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first table can be named a second table, and similarly, a second table can be named a first table without departing from the scope of the various described embodiments. Both the first table and the second table are tables, but they are not the same table.

[0151] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0152] The chemical production safety monitoring method provided in the embodiments of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). The embodiments of the present application do not impose any restrictions on the specific type of terminal devices.

[0153] For example, the terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a TV set-top box (STB), customer premise equipment (CPE) and / or other devices for communicating on a wireless system and a next-generation communication system, such as a mobile terminal in a 5G network or a mobile terminal in a future evolved Public Land Mobile Network (PLMN) network.

[0154] As an example and not a limitation, when the terminal device is a wearable device, the wearable device can also be a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are full-featured, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0155] Figure 9 This is a schematic diagram of the structure of a terminal device provided by an embodiment of the present application. Figure 9 As shown, the terminal device 9 of this embodiment includes: at least one processor 90 ( Figure 9 Only one is shown), a memory 91, wherein the memory 91 stores a computer program 92 that can be run on the processor 90. When the processor 90 executes the computer program 92, the steps in the above-mentioned chemical production safety monitoring method embodiments are implemented, such as Figure 1 Alternatively, when the processor 90 executes the computer program 92, the functions of the modules / units in the above-mentioned system embodiments are realized, for example, Figure 8Functions of modules 810 to 840 are shown.

[0156] The terminal device 9 can be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device can include, but is not limited to, a processor 90 and a memory 91. It can be understood by those skilled in the art that Figure 9 It is only an example of the terminal device 9 and does not constitute a limitation on the terminal device 9. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include an input and sending device, a network access device, a bus, etc.

[0157] The processor 90 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0158] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as a hard drive or memory of the terminal device 9. The memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 91 may include both an internal storage unit of the terminal device 9 and an external storage device. The memory 91 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 91 may also be used to temporarily store data that has been sent or is about to be sent.

[0159] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0160] An embodiment of the present application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, the terminal device implements the steps of any of the above-mentioned method embodiments.

[0161] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0162] An embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0163] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the processes in the above-mentioned embodiment method by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0164] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0165] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0166] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0167] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A chemical production safety monitoring method, characterized in that: include: Obtain chemical production environment information, chemical production equipment status information, and chemical production safety index information; Generate target chemical production feature information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information feature extraction model; Generating chemical production monitoring information according to the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors; Based on the chemical production monitoring information and chemical production safety index information, chemical production risk level characterization information is generated, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

2. The chemical production safety monitoring method according to claim 1, characterized in that: The preset chemical production information feature extraction model includes a plurality of preset chemical production information feature extraction sub-models, a plurality of preset chemical production information feature extraction sub-model selection functions, and a plurality of preset chemical production information feature enhancement functions; wherein the preset chemical production information feature extraction sub-models correspond one to one with the preset chemical production information feature extraction sub-model selection functions; The step of generating target chemical production feature information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information feature extraction model specifically includes: Obtaining multiple chemical production information feature extraction sub-model selection weight information based on the chemical production environment information, the chemical production equipment status information, and multiple preset chemical production information feature extraction sub-model selection functions; Standardizing the selection weight information of the plurality of chemical production information feature extraction sub-models to obtain standardized selection weight information of the plurality of chemical production information feature extraction sub-models; Calculating multiple chemical production information feature variable information based on the chemical production environment information, chemical production equipment status information, and multiple preset chemical production information feature extraction sub-models; Standardizing and selecting weight information based on the plurality of chemical production information feature extraction sub-models, performing weighted summation on the plurality of chemical production information feature variable information, and generating initial chemical production feature information; Target chemical production characteristic information is generated based on the initial chemical production characteristic information and a plurality of preset chemical production information characteristic enhancement functions.

3. The chemical production safety monitoring method according to claim 2, characterized in that: The plurality of preset chemical production information feature enhancement functions include a preset first chemical production information feature enhancement function, a preset second chemical production information feature enhancement function, a preset third chemical production information feature enhancement function, and a preset fourth chemical production information feature enhancement function; The step of generating target chemical production characteristic information based on the initial chemical production characteristic information and a plurality of preset chemical production information characteristic enhancement functions specifically includes: According to the initial chemical production characteristic information, the preset first chemical production information characteristic enhancement function, the preset second chemical production information characteristic enhancement function, and the preset third chemical production information characteristic enhancement function, the first chemical production characteristic enhancement representation information, the second chemical production characteristic enhancement representation information, and the third chemical production characteristic enhancement representation information are calculated; Calculating chemical production feature enhancement weight information based on the first chemical production feature enhancement representation information and the second chemical production feature enhancement representation information; Target chemical production feature information is generated based on the chemical production feature enhancement weight information and the third chemical production feature enhancement representation information.

4. The chemical production safety monitoring method according to claim 1, characterized in that: The plurality of preset chemical production feature coding vectors include a preset chemical production monitoring local feature coding vector and a preset chemical production monitoring long-range feature coding vector; The plurality of preset chemical production monitoring feature mapping vectors include a preset chemical production monitoring feature search mapping vector, a preset chemical production monitoring feature classification mapping vector, a preset chemical production monitoring feature semantic mapping vector, and a plurality of preset chemical production monitoring mapping feature reconstruction vectors; The step of generating chemical production monitoring information based on the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors specifically includes: Obtaining a chemical production local feature coding vector based on the target chemical production feature information and a preset chemical production monitoring local feature coding vector; Obtaining a chemical production long-range feature coding vector based on the target chemical production feature information and a preset chemical production monitoring long-range feature coding vector; Performing interleaving and splicing processing on the chemical production local feature coding vector and the chemical production long-range feature coding vector to obtain a chemical production feature coding vector; Performing a convolution calculation based on the chemical production feature coding vector and a preset chemical production monitoring feature search mapping vector to obtain chemical production search mapping feature vector information; Performing a convolution calculation based on the chemical production feature coding vector and a preset chemical production monitoring feature classification mapping vector to obtain chemical production classification mapping feature vector information; Performing convolution calculation based on the chemical production feature coding vector and the preset chemical production monitoring feature semantic mapping vector to obtain chemical production semantic mapping feature vector information; Performing inner product operation and dimensionality reduction processing on the chemical production search mapping feature vector information and the chemical production classification mapping feature vector information to obtain chemical production mapping feature intermediate variable information; Performing fusion processing on the chemical production mapping feature intermediate variable information and the chemical production semantic mapping feature vector information to obtain chemical production mapping feature vector information; Chemical production monitoring information is generated according to the chemical production mapping feature vector information and a plurality of preset chemical production monitoring mapping feature reconstruction vectors.

5. The chemical production safety monitoring method according to claim 4, characterized in that: The plurality of preset chemical production monitoring mapping feature reconstruction vectors include a preset first chemical production monitoring mapping feature combination vector, a preset first chemical production monitoring mapping feature transformation vector, a preset second chemical production monitoring mapping feature combination vector, and a preset second chemical production monitoring mapping feature transformation vector; The step of generating chemical production monitoring information based on the chemical production mapping feature vector information and a plurality of preset chemical production monitoring mapping feature reconstruction vectors specifically includes: generating initial chemical production mapping feature combination information according to the chemical production mapping feature vector information and a preset first chemical production monitoring mapping feature combination vector; generating initialization chemical production mapping feature reconstruction information according to the initialization chemical production mapping feature combination information and the preset first chemical production monitoring mapping feature transformation vector; generating target chemical production mapping feature combination information based on the initial chemical production mapping feature reconstruction information and a preset second chemical production monitoring mapping feature combination vector; generating target chemical production mapping feature reconstruction information according to the target chemical production mapping feature combination information and a preset second chemical production monitoring mapping feature transformation vector; The target chemical production mapping feature reconstruction information is subjected to feature space conversion processing to generate chemical production monitoring information.

6. The chemical production safety monitoring method according to claim 1, characterized in that: The chemical production monitoring information includes chemical production environment temperature monitoring information, chemical production environment pressure monitoring information and chemical production equipment operation status monitoring information; The chemical production safety index information includes chemical production environment temperature standard interval information, chemical production environment pressure standard interval information and multiple chemical production equipment operating status characterization standard value information; The step of generating chemical production risk level characterization information based on the chemical production monitoring information and the chemical production safety index information, and performing chemical production safety monitoring using the chemical production risk level characterization information, specifically includes: Normalizing the chemical production environment temperature monitoring information, the chemical production environment pressure monitoring information, and the chemical production equipment operation status monitoring information to generate a plurality of normalized chemical production safety monitoring information; Calculating and obtaining a plurality of chemical production safety monitoring prediction information based on the plurality of chemical production safety monitoring normalized information and a plurality of preset chemical production safety monitoring information prediction calculation functions; The multiple chemical production safety monitoring prediction information are matched and processed with the chemical production environment temperature standard interval information, the chemical production environment pressure standard interval information and the multiple chemical production equipment operation status characterization standard value information to generate chemical production risk level characterization information, so as to carry out chemical production safety monitoring through the chemical production risk level characterization information.

7. The chemical production safety monitoring method according to claim 1, characterized in that: The plurality of preset chemical production safety monitoring information prediction calculation functions include a plurality of preset chemical production safety monitoring information prediction weight parameters and a plurality of preset chemical production safety monitoring information prediction bias parameter information; The plurality of preset chemical production safety monitoring information prediction weight parameters include a preset first chemical production safety monitoring information prediction weight parameter, a preset second chemical production safety monitoring information prediction weight parameter, and a preset third chemical production safety monitoring information prediction weight parameter; The plurality of preset chemical production safety monitoring information prediction bias parameter information includes preset first chemical production safety monitoring information prediction bias parameter information, preset second chemical production safety monitoring information prediction bias parameter information, and preset third chemical production safety monitoring information prediction bias parameter information; The step of calculating and obtaining a plurality of chemical production safety monitoring prediction information based on the plurality of chemical production safety monitoring normalized information and a plurality of preset chemical production safety monitoring information prediction calculation functions specifically includes: Calculating a plurality of first chemical production safety monitoring information prediction feature variables based on the plurality of chemical production safety monitoring normalized information and a preset first chemical production safety monitoring information prediction weight parameter; Calculating a plurality of first chemical production safety monitoring information prediction feature bias variables based on the plurality of first chemical production safety monitoring information prediction feature variables and preset first chemical production safety monitoring information prediction bias parameter information; Calculating a plurality of second chemical production safety monitoring information prediction feature variables based on the plurality of first chemical production safety monitoring information prediction feature bias variables and a preset second chemical production safety monitoring information prediction weight parameter; Calculating a plurality of second chemical production safety monitoring information prediction feature variables and preset second chemical production safety monitoring information prediction bias parameter information to obtain a plurality of second chemical production safety monitoring information prediction feature bias variables; Calculating a plurality of third chemical production safety monitoring information prediction feature variables based on the plurality of second chemical production safety monitoring information prediction feature bias variables and a preset third chemical production safety monitoring information prediction weight parameter; Calculating the plurality of third chemical production safety monitoring information prediction feature variables and the preset third chemical production safety monitoring information prediction bias parameter information to obtain a plurality of third chemical production safety monitoring information prediction feature bias variables; Performing hyperbolic tangent transformation on the plurality of third chemical production safety monitoring information prediction feature bias variables to obtain chemical production monitoring feature prediction variables; Obtaining a plurality of chemical production safety monitoring prediction feature information based on the first chemical production safety monitoring information prediction feature bias variable, the second chemical production safety monitoring information prediction feature bias variable, the chemical production monitoring feature prediction variable, and preset chemical production monitoring feature weight information; Linear transformation is performed on the plurality of chemical production safety monitoring and prediction feature information to obtain a plurality of chemical production safety monitoring and prediction information by calculation.

8. A chemical production safety monitoring system, characterized in that: include: Chemical production information acquisition module, used to obtain chemical production environment information, chemical production equipment status information and chemical production safety index information; a target chemical production characteristic information generation module, configured to generate target chemical production characteristic information based on the chemical production environment information, chemical production equipment status information, and a preset chemical production information characteristic extraction model; a chemical production monitoring information generation module, configured to generate chemical production monitoring information based on the target chemical production characteristic information, a plurality of preset chemical production characteristic coding vectors, and a plurality of preset chemical production monitoring characteristic mapping vectors; The chemical production risk level characterization information generation module is used to generate chemical production risk level characterization information based on the chemical production monitoring information and chemical production safety index information, so as to perform chemical production safety monitoring through the chemical production risk level characterization information.

9. A terminal device, characterized in that: The terminal device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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